The Biomedical Image Analysis and Services Section (BIRSS) is committed to providing computational and engineering expertise to a variety of clinical and biomedical informatic activities at NIH. Specifically, biomedical imaging research in PET, ultrasound, CT, MRI, microscopy, cancer research, and neural dysfunction have been supported extensively. To advance and empower scientific research in the NIH intramural program, CIT has developed and continues to enhance a sophisticated open source, platform-independent, n-dimensional, extensible image processing and visualization application. The MIPAV (Medical Image Processing Analysis and Visualization) is an application that enables quantitative analysis and visualization of biomedical imaging modalities (from micro to macro) and is used by researchers at NIH and around the world. At NIH, MIPAV has been used to analyze anatomical structures in CT datasets, analysis of MRI datasets for NIMH, and has been used by NCI for the analysis of 2D and 3D microscopic samples. In addition, we support the development of major components of the National Database for Autism Research (NDAR) project which is a collaborative biomedical informatics system created by the National Institutes of Health to provide a national resource to support and accelerate research in autism. NDAR is a collection of information systems supporting the full range of autism research activities, including genomic, imaging, laboratory, clinical, and behavioral data sources. It provides the core technology for a data warehouse, and a centralized source for common measures and their documentation. NDAR supports large-scale, multi-site projects as well as pilot studies and basic science investigations. In collaboration with the National Institute of Neurological Disorders and Stroke (NINDS), BIRSS also develops two infomatics systems in support of Traumatic Brain Injury (TBI) research and the Parkisnons Disease Biomarker Program (PDBP). Traumatic brain injury (TBI) is a major medical problem for both military and civilian populations. There are many critical gaps in our knowledge regarding how to diagnose and treat people who sustain a TBI. High priority gaps include the need for an objective diagnosis for mild TBI, biomarkers to track recovery or progression of injury, a biologically-based classification system, and comparative effectiveness research to determine which treatments are effective and for whom. To address these gaps, as well as other important questions on how to improve outcomes, the National Institutes of Health (NIH), in partnership with the Department of Defense (DoD), is building a secure, centralized informatics system (database) for traumatic brain injury research. It will serve as a central repository for new data, link to current databases and allow valid comparison of results across studies. The database builds upon a larger effort to create common data elements for the study of traumatic brain injury which are essentially definitions and guidelines about the kinds of data that should be collected, and how to collect these data in clinical studies. The Common Data Elements project emerged from a collaborative interagency effort involving over 50 American and European universities and several federal agencies, including NIH, the DoD, the Department of Veterans Affairs, the Center for Disease Prevention, and the National Institute on Disability and Rehabilitation Research within the Department of Education. Thus, the TBI informatics system is called the Federal Interagency TBI Research (FITBIR) database to acknowledge the interagency participation and shared interests. It is envisioned that FITBIR will serve as a repository for TBI research supported by multiple federal agencies and consolidate high quality, uniformly collected, and contemporary data that can be accessed and analyzed by scientific experts. The goal of the PDBP is to support new and existing research and resource development promoting biomarker discovery for Parkinson's Disease. Although our understanding of the biology and genetics associated with Parkinson's disease (PD) is advancing rapidly, gaps remain between promising laboratory discoveries and the realization of treatments that will cure or slow progression of PD. To address the needs of the PD community, NINDS has established the PDBP program focused on promoting the discovery of biomarker candidates for early detection and measurement of disease progression. The PDBP will coordinate the efforts of multiple stakeholders through a common data management resource and web portal. The PDBP will serve as a multi-faceted platform for: 1. Integrating existing biomarker efforts 2. Standardizing data collection and management across these efforts 3. Accelerating the discovery of new biomarkers 4. Fostering and expanding collaborative opportunities for all stakeholders